water based TiO2 nanofluids

ICHMT-03468; No of Pages 11 International Communications in Heat and Mass Transfer xxx (2016) xxx–xxx

Contents lists available at ScienceDirect

International Communications in Heat and Mass Transfer journal homepage: www.elsevier.com/locate/ichmt

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a r t i c l e

Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia Automotive Engineering Centre, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia d Tarbiat Modares University, Tehran, Iran b c

i n f o

a b s t r a c t

Nanofluid as a new brand of cooling fluid consisting of nanometer-sized particles dispersed in base fluid. In this study, nanofluids have been prepared by dispersing TiO2 nanoparticles in different base fluids such as 20:80% and 30:70% by volume of BioGlycol (BG)/water (W) mixtures. Thermal conductivity and viscosity experiments have been conducted in temperatures between 30 °C and 80 °C and in volume concentrations between 0.5% and 2.0%. Results show that thermal conductivity of nanofluids increases with increase of volume concentrations and temperatures. Similarly, viscosity of nanofluid increases with increase of volume concentrations but decreases with increase of temperatures. The maximum thermal conductivity enhancement among all the nanofluids was observed for 20:80% BG:W nanofluid about 12.6% in the volume concentration of 2.0% at a temperature of 80 °C. Correspondingly among all the nanofluids maximum viscosity enhancement was observed for 30:70% BG:W nanofluid about 1.53-times in the volume concentration of 2.0% at a temperature of 70 °C. The classical models and semi-empirical correlations failed to predict the thermal conductivity and viscosity of nanofluids with effect of volume concentration and temperatures. Therefore, a nonlinear correlation has been proposed with 5% maximum deviation for the estimation of thermal conductivity and viscosity of nanofluids. © 2016 Published by Elsevier Ltd.

Available online xxxx Keywords: Nanofluids BioGlycol Titanium oxide Thermal conductivity Viscosity

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1. Introduction

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Nanofluids, colloidal dispersions of nanoparticles in liquid have great potential as coolants owing to their higher thermal conductivity. The motivation for nanofluids can be traced back to Maxwell's [1] prediction of improving thermal conductivity of liquids using solid particles. Certainly the heat-transfer processes have an effective role in most of the areas of industrial engineering, represented in the power generation, air conditioning, automotive, solar collector and chemical processors [2–8]. Over the past decades, there had been a dramatic increase in using water (W), ethylene glycol (EG) and propylene glycol (PG) based nanofluids due to their vast applications in the transfer of thermal energy [9–13]. Masuda et al. [14] have initiated studies on the effect of Al2O3, SiO2 and TiO2 nanoparticles dispersed in water on the thermal conductivity and viscosity of the nanofluid. Murshed et al. [15] investigated the viscosities of water based nanofluid of 15 nm TiO2 nanoparticles. The results showed that the viscosity increase with the volumetric

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M.Kh. Abdolbaqi a, Nor Azwadi Che Sidik b,⁎, Amir Aziz a, Rizalman Mamat a,c, W.H. Azmi a,c, Mohammad Noor Afiq Witri Muhammad Yazid b, G. Najafi d

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An experimental determination of thermal conductivity and viscosity of BioGlycol/ water based TiO2 nanofluids☆

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☆ Communicated by W.J. Minkowycz ⁎ Corresponding author. E-mail address: [email protected] (N.A.C. Sidik).

loading of nanoparticles and slightly high when compared with the data of Masuda et al. [14]. According to Choi [16], the recent two decades, nanofluids have attracted wide attention as exhibited by the enormous increment in the publications on this subject. It is noteworthy that the majority of these studies adopted water-based nanofluids that were often tested within the surrounding temperatures, followed by many other studies until recently. Several investigative studies have been conducted on the role of ethylene glycol based TiO2 nanofluids in heat transfer enhancement [17–21]. Fan et al. [19] investigate the thermal conductivity at 303 K for the concentrations 0.5, 2.0, and 4.0 wt.% for TiO2/EG nanofluids and their corresponding viscosity, confirming a Newtonian behavior and the expected increase of viscosity with nanoparticle concentration. Chen et al. [20] have also found a Newtonian behavior for TiO2/EG nanofluids containing 0.5, 1.0, 2.0, 4.0, and 8.0 wt.% spherical nanoparticles at 293.15 to 333.15 K and a relative viscosity dependent on particle concentration in a non-linear manner without temperature dependence. On the other hand, Lee et al. [21] have determined temperature-independent thermal conductivity enhancements up to 16% for 5.5 vol.% TiO2/EG nanofluids constituted by nanoparticles with rutile and anatase phases. The enhancement of density in relation to

http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007 0735-1933/© 2016 Published by Elsevier Ltd.

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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M.K. Abdolbaqi et al. / International Communications in Heat and Mass Transfer xxx (2016) xxx–xxx

T1:1

Nomenclature

T1:2 T1:3 T1:4 T1:5 T1:6 T1:7 T1:8 T1:9 T1:10 T1:11 T1:12 T1:13 T1:14 T1:15 T1:16 T1:17 T1:18 T1:19 T1:20 T1:21 T1:22

ATC Cμ BG EG PG D

T1:23 T1:24 T1:25 T1:26 T1:27 T1:28 T1:29 T1:30 T1:31 T1:32

Greek symbols ϕ Volume concentration, % ϕ Volume fraction, ϕ = (ϕ/100) ϕa Volume fraction of aggregates ϕi Volume fraction of agglomerates, ϕi = (ra/r)D − 3 ρ Density, kg/m3 σ Electrical conductivity α Conductivity ratio, α = (σp/σbf) ω Weight concentration in percent

T1:33 T1:34 T1:35 T1:36 T1:37 T1:38

Subscripts bf Base fluid eff Effective nf Nanofluid p Particle

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2. Experimental setup

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2.1. Nanofluid preparation

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Titanium oxide TiO2 water based nanofluid contains anatase TiO2 nanoparticles with 99% purity procured from US Research Nanomaterials, Inc. is used in the experiments after appropriate dilution and mixing with BioGlycol/water. The TiO2 nanoparticles have thermal conductivity of 8.6 W/m K, density of 4175 kg/m3 and average particle size is 50 nm [38–40]. It was supplied with an initial concentration of 40% by weight at a pH of 6.5. [39]. The nanofluid supplied in weight concentration ω is converted to volume concentration ϕ with Eq. (1). The volume of distilled water ΔV to be added for attaining a desired concentration ϕ2 is evaluated with Eq. (2) with the values of V1 and ϕ1 known a priori [3]:

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the base fluid is also higher for rutile nanofluids, reaching values of 3.8% at the highest concentration. These increments with the concentration are almost temperature and pressure independent. In spite of its versatility, the use of PG as the base liquid has been rarely investigated [22–24]. Recently Palabiyik et al. [25] studied propylene glycol based nanofluids of both Al2O3 and TiO2 nanoparticles with a temperature range of 20 to 80 °C and volume concentrations of 1, 6 and 9%. The results showed that the enhancement of thermal conductivity is in a non-linear form as a function of concentration, and independent with temperature. Vajjha et al. [26] studied the viscosities of five nanoparticles (Al2O3, CuO, SiO2, TiO2, and ZnO) dispersed in a base fluid of 60:40 PG/W. The results illustrated the these nanofluids exhibit a non-Newtonian behavior within a lower temperature range of 243 K–273 K and a Newtonian behavior within the higher temperature range of 273 K–363 K. In a different study, Suganthi and Rajan [27] investigated experimentally the influence of ZnO dispersed in 20:80% of PG:W with volume concentrations of lower than 2% and temperature of 15 to 50 °C. The results showed that the thermal conductivity revealed better enhancements at lower temperatures. However, a number of studies have found that the dispersion and stability are the essential characteristics in the enhancement of the thermo-physical properties of nanofluids especially for thermal conductivity [28–31]. Uniform dispersion and stable suspension of nanoparticles in the liquids are the main keys to successful applications of nanofluids. The final

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TEC HS Kbf kBG kr μbf μnf μr m r ra ka n

Temperature compensation Viscosity enhancement Bio glycol Ethylene glycol Propylene glycol Fractal index, which has an average value of 1.8 for nanofluids Thermo-electrical conductivity ratio Hashin–Shtrikman model Thermal conductivity of base fluid, W/m K Thermal conductivity of bio glycol, W/m K Thermal conductivity ratio = knf/kbf Viscosity of base fluid, mPa s Viscosity of nanofluid fluid, mPa s Viscosity ratio = μnf/μbf Mass, gram Radius of primary nanoparticles, nm Radius of aggregates nanoparticles, nm Thermal conductivity of agglomerates Empirical shape factor

properties of nanofluids were determined by the quality of the dispersed state of the suspension [4,32–34]. Many researchers have reported the necessity of proper dispersion of nanofluids and various dispersion techniques [35]. They also measured the thermal conductivity as a function of ultra-sonication (physical technique) time and showed that long hours of ultra-sonic dispersion were required to improve particle dispersion [36]. However, BioGlycol (BG) showed more advantages compared to water, for instance a much lower freezing point and a much higher boiling point (−46 °C to 177 °C). Moreover, one of the BG attributes is that it has a lower thermal conductivity than water to about one-third. Additionally BioGlycol solution is produced domestically, renewable sourced fluid, non-toxic, and at low temperatures that provided 30% lower viscosity compared to propylene glycol which is petroleum-derived [37]. It also has greater thermal stability while possessing similar or better thermo-physical properties compared to propylene and ethylene glycols. It offers better performance than propylene glycol while giving its users an environmentally safer product than ethylene glycol [37]. Literature reviews have indicated that there is no academic report that has been published so far using BioGlycol in nanofluids. Therefore, this study aims to investigate experimentally the thermal conductivity, viscosity and stability of 20:80% and 30:70% BioGlycol:water mixture based TiO2 nanofluid. As well as to develop thermal conductivity and viscosity models based on present study data of 0.5 to 2.0% volume concentration and the temperature range of 30 to 80 °C. The thermal conductivity and viscosity data obtained in the present work are compared with sixteen models and semi-empirical correlations available in the literature.

ϕ¼


1−

ωρw ω  ω ρ þ ρ 100 p 100 w

ΔV ¼ ðV 2 −V 1 Þ ¼ V 1

  ϕ1 −1 ϕ2

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ð1Þ 145 146

ð2Þ 148

The characterization of TiO2 nanoparticles is obtained by the field emission scanning electron microscopy (FESEM) technique [41]. The image of FESEM at a magnification of 300,000 illustrated that the TiO2 nanoparticles average size of 50 nm and the shape is observed to be spherical as shown in Fig. (1). The experiments were conducted using 0.5, 1.0, 1.5 and 2.0% volume concentrations of TiO2 nanofluids with two mixture ratios of BG:W in 20:80% and 30:70% by volume as shown in Fig. (2). The procured TiO2 nanofluid was prepared to a new concentration by dilution techniques. The technique was applied successfully by the previous researchers in their heat transfer evaluation for TiO2 nanofluids [39,40,42–44]. The reasons for choosing TiO2 nanoparticles are that TiO2 is currently regarded as a safe material for human being and animals, TiO2 nanoparticles are produced in large

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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The thermal conductivity of the samples was measured using KD2 Pro thermal property analyzer of Decagon Devices, Inc., USA. The data were collected for a temperature range of 30 to 80 °C after two hours of the sonication process. Various investigators used KD2 pro thermal property analyzer in their measurements of thermal conductivity [52–57]. This instrument applied the transient hot-wire method. The present measurement method allowed the thermal conductivity measurement of nanofluids with minimum free convection effects. The experiment was performed five times for each sample and condition, and a data point reported in this study thus represents an average of five measurements with an estimated error of ±1.2%.

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2.3. Thermal conductivity measurement

industrial scale, and metal oxides such TiO2 are chemically more stable than their metallic counterparts [20,45].

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2.2. Stability of nanofluid

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In order to prepare stable nanofluids and reduce the size of agglomerates, sonication was applied using an ultra-sonicator. Nanofluids were prepared in volumes of 100 mL for each volume concentration and exposed to the sonicator for 2 h. After that, the nanofluids were very stable throughout the measuring process. Evaluation of the stability of the studied nanofluids has been examined at room temperature with UV– vis spectrophotometer (Genesys 10S UV–vis Spectrophotometer). Many researchers have used UV–vis spectrophotometer to evaluate the stability of the nanofluids [46–49]. Stability measurement of nanofluids with UV–vis spectrophotometer was first proposed by Jiang et al. [50] as an extension of the sediment time method. The most important issues that need to be taken into account are peak scanning and standard preparation of nanofluid as reported by [49,50]. Literature review showed that a standard preparation method should be a diluted suspension of around (0.01–0.02 wt.%) so that UV–vis spectrophotometer can detect the wavelengths [51]. Therefore, this research came out with diluted concentrations of two samples of BG:W (20:80% and 30:70%) based TiO2 nanofluid of 0.3 vol.% to evaluate the stability of nanofluids. Hence 0.3% volume concentration in BG:W (20:80% and 30:70%) can be represented by (0.0124 wt.% and 0.0125 wt.%) in weight concentration respectively.

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3.1. Thermal conductivity models

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A considerable number of models and correlations have been proposed in view of explaining the thermal conductivity behavior of suspensions containing small solid particles. Some of those theories are analyzed and compared with current experimental findings. Maxwell [1] was the first to propose the model to determine the effective electrical or thermal conductivity of suspensions containing solid particles. This model may be applied to statistically homogeneous and lowvolume fraction liquid–solid suspensions with randomly dispersed, uniformly sized and non-interacting spherical particles:

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3. Mathematical models

knf kbf

  kp þ 2kbf −2ϕ kbf −kp   ¼ kp þ 2kbf þ ϕ kbf −kp

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ð3Þ

where kp, is the thermal conductivity of the nanoparticles, and ϕ is the volume fraction of nanoparticles in the mixture. It is noted that the Maxwell equation is not a function of temperature. Since then several models were introduced in order to take an account of Brownian motion of nanoparticles [60,61], liquid layering around them [62], ballistic heat transport in nanoparticles and the particle's geometry [63–66]. However, it is largely accepted that the thermal conductivity enhancement can

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The Viscosity of the nanofluids was measured using Brookfield LVDV-III Ultra Rheometer. Several investigators were used Brookfield Rheometer in their measurement of viscosity [38,58,59]. The viscosity was measured in temperatures between 30 °C and 80 °C and the values were recorded at steady state conditions and 30 min was allowed to stabilize the temperature.

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Fig. 1. FESEM image of dry TiO2 nanoparticle at ×140,000 magnification.

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2.4. Viscosity measurement

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Fig. 2. Samples of BioGlycol–water based TiO2 nanofluid.

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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  knf ka þ 2kbf −2ϕa kbf −ka   ¼ kbf ka þ 2kbf þ ϕa kbf −ka 234

ð4Þ

where ϕa = (ra/r)3 − D and ka is to be determined from the Bruggeman model [70] in Eq. (5):   kp ka 1 ¼ ð3ϕi −1Þ þ ð3ð1−ϕi Þ−1 kbf 4 kbf

1 ) kp kp 2 2 þ ð3ð1−ϕ1 Þ−1Þ þ 8 þ ð3ϕi −1Þ kbf kbf

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kseries

ð1−ϕÞ ϕ ¼ þ kbf kp

1 ¼ ð1−ϕÞkbf þ ϕkp kparallel

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ð6Þ

ð7Þ

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More complex Hashin–Shtrikman model (HS) [74] was widely used to estimate upper and lower limits of effective thermal conductivity of nanofluids according to the formula in Eq. (8): !   3ϕ kp −kbf   ≤knf ≤kp  1þ 3kbf þ ð1−ϕÞ kp −kbf

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¼ ½1 þ 2:5ϕ

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ð9Þ 275

Brinkman [77] considered the higher-order coefficients neglected by Einstein in an effort to validate his equation to higher particle volume 276 fraction less than 4.0%. 277 " # μ eff 1 ¼ μ bf ð1−ϕÞ2:5

ð10Þ 279

Batchelor [78] improved the correlation of Einstein by considered the effect of Brownian motion of particles for an isotropic suspension 280 of rigid and spherical particles. 281 ð11Þ 283

Thomas and Muthukumar [79] derived the effective viscosity of a dilute suspension of hard spheres from fully hydrodynamic interactions 284 involving three spheres. 285 i μ eff h ¼ 1 þ 2:5ϕ þ 4:8292ϕ2 þ 6:4028ϕ3 þ … μ bf

ð12Þ 287

Nguyen et al. [80] developed an equation that is applicable to predict the viscosity of water based Al2O3 nanofluid of 0–12.0% volume 288 concentration. 289

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where ϕi is the solid volume fraction of agglomerates given by ϕi = (ra/r)D−3. ra and r are the radius of aggregates and primary nanoparticles, respectively. The term D is the fractal index, which has an average value of 1.8 for nanofluids assuming diffusion limited aggregation. Moreover, some authors [71,72] consider mean-field boundary theory as the best suited model for estimating thermal conductivity enhancement. There are two main models in the mean field theory. One is the simple series and parallel model which is based on the configuration of nanoparticles relative to the direction of heat flux in a nanofluid [73]. According to the theory, the effective thermal conductivity is calculated assuming series and parallel configuration of nanoparticles in base fluid are as follows:

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μ bf

i μ eff h ¼ 1 þ 2:5ϕ þ 6:5ϕ2 μ bf

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ð5Þ

μ eff

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Einstein model Eq. (9) is the mostly referred equation to predict the viscosity of nanofluids and this model applicable for drawback is that it predicts only very low nanoparticle concentrations (ϕ ≤ 0.02%). considering the hydrodynamics around an isolated sphere. Ever since this work was published, many researchers developed several equations to extend Einstein's theory to higher particle volume fractions.

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be best described by nanoparticle structuring [54] and the manner of particle packing in the matrix [67]. Thus, Hamilton and Crosser [68] modified Maxwell's model and showed the effect of particle shape and particle volume fraction on thermal conductivity of suspensions. On the other hand, the size effects of nanoparticles are not included in both models. Considering that nanoparticles in nanofluids are mostly in the form of aggregates. Chen et al. [69] used to modify the conventional form of Hamilton-Crosser model. It introduced the concept of the effective volume fraction of aggregates ϕa and replaced the term kp with ka, which is the thermal conductivity of agglomerates as shown by Eq. (4):

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M.K. Abdolbaqi et al. / International Communications in Heat and Mass Transfer xxx (2016) xxx–xxx

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 ! 3ð1−ϕÞ kp −kbf   1− 3kp þ ϕ kp −kbf

μ nf μ bf

 ¼ 0:904e0:148ϕ

ð13Þ 291

Maiga et al. [81] proposed a model for viscosity of ethylene glycol base Al2O3 nanofluid of 0–5% volume concentration. 292 μ nf μ bf

h i ¼ 1−0:19ϕ þ 306ϕ2

ð14Þ 294

4. Results and discussion 4.1. Stability of nanofluid

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Physically, the upper HS bound corresponds to a nanocluster matrix with spherical inclusions of fluid regions while the lower HS bound assumes well dispersed nanoparticles in the base fluid [75]. HS lower bound, which is the left hand side of the inequality, is identical to Maxwell's equation. In an attempt to resolve the controversy of thermal conduction in nanofluids, Keblinski et al. [71] analyzed a large number of experimental data published on nanofluids. It was demonstrated that almost all the literature data falls within HS bounds and showed that the well-dispersed nanofluids follows the classical Maxwell relationship.

The stability of the different nanofluids was measured with UV–vis spectrophotometer (Genesys 10S UV–vis Spectrophotometer). Each type of nanofluid sample was scanned in 5 min with 1.0 nm interval to measure the suspension concentration with increasing sediment time at room temperature. The wavelength range of light was 190–1100 nm. Fig. (3) shows that the absorbance of functionalized TiO2 decreases from (4.311) to (3.848) with wave length of 318 and 314 respectively. Knowing that the increasing amount of dispersed TiO2 will result in increasing the absorbance, it can be concluded that 30:70% BG:W have more tendency for agglomeration/precipitation. Higher specific surface area of 20:80% compared to that of 30:70% is another reason for higher absorbance in TiO2 suspension.

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4.2. Thermal conductivity enhancement

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The early studies for the determination of viscosity of suspended sphere particles in liquids have been undertaken by Einstein [76]. The

In order to investigate the effectiveness of BG:W as a base fluid a 309 comparison of the standard data of BioGlycol by Dynalene [37] with 310

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Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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  Enhancement ¼ knf –kbf 100=kbf

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Thermal conductivity enhancements obtained from the published theoretical models are illustrated in Fig. 5(a,b). The models were compared with current experimental data for BG:W of 20:80% and 30:70% based TiO2 nanofluids of 0.5, 1.0, 1.5 and 2.0% volume concentrations

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propylene glycol and ethylene glycol by ASHRAE [82] at the same mixture ratio of fluid/Water (20:80% and 30:70%) with temperature range of (30–80) °C, BG/W provide 3.1% higher thermal conductivity than PG/W [82] while EG/W [82] demonstrate 0.7% higher thermal conductivity than BG/W as illustrate in Fig. 4. At the stage of instrument calibration, the measured thermal conductivity data obtained for nanofluids were compared with available literature data of BioGlycol by Dynalene [37]. In the measured temperature range, the obtained thermal conductivity of all fluids was found ±0.7% deviation with reference values. The enhancement of thermal conductivity increased with an increase of nanoparticle volume concentration and temperature, as well as the enhancement of BG:W in 20:80% mixture ratio was higher than 30:70%. Furthermore Eq. (15) used to estimate the enhancement of thermal conductivity based on the measured thermal conductivity data.

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Fig. 3. UV–vis spectrophotometer evaluation of TiO2 nanofluid.

Fig. 4. Comparison of thermal conductivity among BioGlycol, propylene glycol and ethylene glycol.

Fig. 5. Comparison of thermal conductivity enhancement with theoretical models.

at 30 °C. Moreover, current experimental data lays between HS bonds. However, the Maxwell model underestimates the thermal conductivity enhancement of TiO2 nanoparticles. In particular, good correlation between experimental results and theoretical prediction according to aggregation models were observed at fairly high particle concentration. Moreover, the series and parallel models appear to be the most ineffective estimation tool for both nanofluids. In fact, it is hard to control the nanoparticle structure and configuration with the existing knowledge and technology. This restricts the series–parallel model from becoming a viable technique. Effect of temperature on thermal conductivity can be explained in Fig. 6(a,b) which presents thermal conductivity against measured temperature. The thermal conductivity of base liquid and nanofluids are increasing with temperature. Hence, it can be deduced that the thermal conductivity of nanofluids is directly proportional with temperature and concentrations of nanoparticles. As seen from Fig. 7(a,b), the thermal conductivity enhancement increases with an increase of temperature and nanoparticle concentration for TiO2 nanofluids. The maximum thermal conductivity enhancement of 20:80% BG:W based 2.0% TiO2 nanofluid is 12.6% at temperature of 80 °C as illustrate in Fig. 7(a). Whereas the maximum thermal conductivity enhancement of using 30:70% is 11% at same conditions as shown in Fig. 7(b). This

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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Fig. 7. Thermal conductivity ratio of BG:W TiO2 nanofluid.

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Fig. 6. Thermal conductivity of BG:W TiO2 nanofluid with temperature variation.

could be attributed to the layering of the base fluid molecules on the surface of the nanoparticles [27].

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4.2.1. Proposed model of thermal conductivity The analysis of variance is a requisite to check the significance of the model [83]. Moreover, this analysis gives clearly how the parameters affect the response and the level of significance of the factors. [84]. Hence, the analysis of variance was implemented to produce nonlinear correlation as a function of volume concentration and temperature. Thus, it gives an accurate description of the thermal conductivity behavior for BG/W nanofluid. The current study of thermal conductivity measurement for TiO2 nanoparticles dispersed in 20:80% and 30:70% of BG:W based fluid. The present experimental data have been compared among several established semi-empirical equations. The thermal conductivity correlations are presented in Table 1. The equations were developed based on an experimental measurement data of nanofluids in different base fluids [48,77–79]. Fig. 8(a) and (b) show comparison between the equations in Table 1 and present thermal conductivity data for TiO2 nanofluids in BG:W at a temperature of 30 °C. However, the equations

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failed to agree with the present BioGlycol data. Therefore, new thermal conductivity of BioGlycol based nanofluid correlation was developed as a function of volume concentration and temperature. The equation was conceived in the form of Eq. (16).

kr ¼

   0:011 knf ϕ 0:042 T ¼ 1:308   100 80 kbf

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ð16Þ 376

The thermal conductivity data of TiO2 nanofluid at different concentration and temperature is subjected to regression. Eq. (16) was obtained with an average deviation of 0.6%, standard deviation of 0.4% and maximum deviation of 2%. Fig. 9 shows the result validation for the BioGlycol thermal conductivity model in Eq. (16). The figure provides the similarities between predicted and experimental results of thermal conductivity of TiO2 nanofluid in BG:W for a wide range of volume concentrations of 0.5 to 2.0% and temperature of 30 to 80 °C. The result shows that the model is able to estimate the thermal conductivity of BioGlycol nanofluids for different concentrations and temperatures within ±2% deviation. The

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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M.K. Abdolbaqi et al. / International Communications in Heat and Mass Transfer xxx (2016) xxx–xxx Table 1 Thermal conductivity models for nanofluids proposed by researchers.

t1:3

References

Correlations

t1:4

Maiga et al. [86]

K nf K bf

¼ 4:97ϕ2 þ 2:72ϕ þ 1

t1:5

Buongiorno [87]

K nf K bf

¼ 1 þ 2:92ϕ−11:99ϕ2

t1:6

Mintsa et al. [57]

K nf K bf

¼ 1 þ 1:72ϕ

t1:7

Jeffrey [88]



  k =k −1 k =k −1 2 k =k −1 2 ¼ 1 þ 3ð kpp =kbf þ2 Þϕ þ 3 kpp =kbf þ2 þ 34 kpp =kbf þ2 ϕ2 bf

bf

390

4.3. Viscosity enhancement

391 Q2 392

In order to study the effectiveness of BG:W as a base fluid a comparison at same mixture ratio fluid/water of (20:80%, 30:70%) and with temperature range of (30–80) °C, BG/W [37] demonstrate 57.3% and 57.5% lower viscosity than PG/W [82] respectively and 54.3%

Fig. 9. Result validation of non-linear thermal conductivity proposed model in Eq. (16).

and 50.8% lower viscosity than EG/W [82] respectively as shown in Fig. (10). Interestingly, viscosity instrument was calibrated by introducing the known viscosity of fluids such as 20:80% and 30:70% BG/W. The experimental values of all fluids were found ±1.1% deviation in comparison with the values obtained from Dynalene [37] at measured temperature range of (30–80) °C. Likewise the viscosity results of 20:80% and 30:70% BG:W nanofluid respectively reveal that viscosity of nanofluids decreases with increase of temperatures, while increases with increase of particle volume concentrations compared to base fluid as shown in Fig. 11(a) and (b). Additionally, viscosity enhancement of 20:80% BG:W based 2.0% volume concentration are 20.5% and 33.8% in temperatures of 30 °C and 80 °C. As well as the viscosity of 30:70% BG:W nanofluid compared to base fluid respectively as illustrated in Fig. 12(a) and (b) the viscosity enhancement for 2.0% volume concentration is 29.8% and 53.4% in temperatures of 30 °C and 60 °C compared to base fluid respectively. It is noteworthy that at the same volume concentration (2.0%) of all nanofluids in low temperature (30 °C), the viscosity enhancement is lower compared to high temperature (80 °C).

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present observations show the capability of the aggregation mechanism to accurately predict the thermal conductivity of well-dispersed nanofluids even at fairly high volume concentrations.

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Fig. 8. Comparison between experimental data and semi-empirical correlations.

Fig. 10. Comparison of viscosity among BioGlycol, propylene glycol and ethylene glycol.

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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Fig. 11. Viscosity of BG:W TiO2 nanofluid with temperature variation.

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Fig. 12. Viscosity ratio of BG:W TiO2 nanofluid.

4.3.1. Predict new correlation of viscosity Similarly, of proposed thermal conductivity correlation the analysis of variance was implemented to produce nonlinear correlation as a function of volume concentration and temperature. Accordingly, it obtains an accurate description of the viscosity behavior for BG/W nanofluid. In the present study, the equations failed to agree with the present BioGlycol data as shown in Fig. 13(a) and (b). Therefore, new viscosity of BioGlycol based nanofluid correlation was developed as a function of volume concentration and temperature. An exponential form was used to derive the viscosity values of nanofluids as a function of temperature and volume concentration. Viscosity correlation Eq. (17) was developed based on 60 data points by assuming that nanofluid viscosity increases and decreases exponentially with particle concentrations and temperature respectively

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μ nf T ¼ 0:918 exp 14:696ϕ þ 0:161 80 μ bf

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A maximum deviation of about 5%, standard deviation about 1.11% and average deviation about 1.2% were observed between the experimental and proposed correlation values for all the nanofluids examined as shown in Fig. 14.

4.4. Effect of property enhancement ratio

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The condition for maximum heat transfer was analyzed with the aid of viscosity and thermal conductivity. The property enhancement ratio (PER) of viscosity to thermal conductivity is given by Eq. (18) According to the analysis of Garg et al. [85] when (PER) is greater than 5.0, the nanofluid does not aid heat transfer enhancement.

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 ðμ r −1Þ K bf μ nf −μ bf   ¼ PER ¼ ðK r −1Þ μ bf K nf −K bf

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ð18Þ 440

The effect of property enhancement ratio observed to be strongly dependent on the changes in the values of viscosity and thermal conductivity. Therefore, the property enhancement ratio illustrated in Fig. 15(a) and (b) predicted the experimental condition of heat enhancement satisfactorily for BG:W 20:80% and 30:70% based TiO2 nanofluid. The PER is 5.0 for TiO2 30:70% BG:W at 2.0% concentration with 60 °C and in agreement with the condition for maximum experimental heat transfer coefficient. This due to greater values of viscosity

Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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Fig. 13. Result validation for non-linear thermal conductivity model in Eq. (17).

Fig. 14. Result validation of non-linear thermal conductivity proposed model in Eq. (16).

Fig. 15. Effect of properties on heat transfer enhancement.

for BG:W 30:70% based TiO2 nanofluids as compared to the values of BG:W 20:80% based TiO2 nanofluids. As well as due to the lower values of thermal conductivity for BG:W 30:70% based TiO2 nanofluids as compared to the values of BG:W 20:80% based TiO2. However BG:W 20:80% based TiO2 nanofluids for all concentrations show lower values of PER comparing with as compared to the values of BG:W 30:70% based TiO2 nanofluids.

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Experimental analysis was conducted for the estimation of thermal conductivity and viscosity of TiO2 nanofluid with influence of particle concentrations, temperatures and base fluids. In order to study the properties with effect of base fluids, two base fluids such as 20:80% and 30:70% BG/W were considered. Based on the obtained results, key findings of this investigation can be summarized as follows:

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• Stable nanofluids of 0.5 to 2.0% volume concentrations were prepared by prolonged ultrasonication processes and without the use of any surfactant. Dispersion stability of the samples was examined by UV– vis spectrophotometer test.

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Please cite this article as: M.K. Abdolbaqi, et al., An experimental determination of thermal conductivity and viscosity of BioGlycol/water based TiO2 nanofluids, Int. Commun. Heat Mass Transf. (2016), http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.07.007

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The financial support by Universiti Malaysia Pahang (UMP) under RDU1403110 and also Automotive Excellence Center (AEC) under RDU1403153 are gratefully acknowledged.

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References

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• The highest thermal conductivity enhancement of 12.6% was observed at 2% volume concentration for BG:W in 20:80% mixture ratio and temperature of 80 °C. The maximum thermal conductivity enhancement up to 11% was found for 30:70% at the same conditions • A new non-linear models based on the aggregation theory using ANOVA has been developed for the thermal conductivity and viscosity of nanofluids as a function of temperature and volume concentration. The models seemed most appropriate with only 5% deviation. • Thermal conductivity enhancement of nanofluid not only depends on the particle concentration and temperature but it also depends on the base fluid thermal conductivity. • Nanofluid prepared in high thermal conductivity base fluid exhibits more enhancement compared to low thermal conductivity base fluid. The viscosity enhancement of 20:80% BG:W based 2.0% volume concentration are 20.5% and 33.8% in temperatures of 30 °C and 80 °C. As well as the viscosity enhancement of 30:70% BG:W for 2.0% volume concentration is 29.8% and 53.4% in temperatures of 30 °C and 60 °C compared to base fluid respectively. • However BG:W 20:80% based TiO2 nanofluids for all concentrations show lower values of PER comparing with as compared to the values of BG:W 30:70% based TiO2 nanofluids.

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